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Department of Statistics

 

Georgy Sofronov

barry_quinn

Formal Name: Georgy Sofronov

Personal title: Dr 

Position: Senior Lecturer

Organisational Unit: Department of Statistics

Telephone: (+61-2) 9850-8544

Fax: (+61-2) 9850-7669

Email: georgy.sofronov@mq.edu.au

Location: E4A 536

 Research interests

  • Markov chain Monte Carlo methods, Cross-Entropy method
  • Linear Mixed Models, Small Area Estimation, Biological models
  • Theory and applications of random processes, optimal stopping rules
  • Sequential analysis, asymptotic theory, change-point problem

Teaching

  • 2014, 2 Semester, STAT821 Multivariate Statistical Analysis
  • 2014, 2013, 2012, 2011, 1 Semester, STAT272 Probability
  • 2014, 1 Semester, STAT830 Prelude to Bioinformatics
  • 2013, 2012, 2011, 1 Semester, ACST601 Stochastic Methods in Finance and Insurance
  • 2012, 2011, 2010, 2 Semester, STAT328/STAT826 Market Research and Forecasting
  • 2011, 2010, 2 Semester, STAT273 Introduction to Probability
  • 2010, 1 Semester, STAT375 Linear Models
  • 2010, 1 Semester, STAT170 Introductory Statistics

Current Administrative Duties

  • Coordinator of the Master of Applied Statistics program
  • Member of the Departmental Learning and Teaching Committee
  • Seminar organiser (to subscribe or unsubscribe to the Department of Statistics seminar mailing list, send me an email message)

Selected publications

  • Priyadarshana, M. W. J. R., Poluhina T., Sofronov, G. (2014) Hybrid Algorithms for Multiple Change-Point Detection in Biological Sequence. In: Sun, C., Bednarz, T., Pham, T.D., Vallotton, P., Wang, D. (Eds.) Signal and Image Analysis for Biomedical and Life Sciences, ISBN 978-3-319-10983-1 (in press).
  • Trubyanov A. B., Sofronov G. Yu., Glotov N. V. (2014). Analysis of Correlation Structure in Bilateral Traits. In: L. I. Weisfeld, A. I. Opalko, N. A. Bome, S. A. Bekuzarova (Eds.) Biological Systems, Biodiversity, and Stability of Plant Communities, ISBN 978-1-77188-064-0 (in press).
  • Glotov N. V., Sofronov G. Yu., Ivanov S. M., Suetina Yu. G., Prokopyeva L. V., Teplykh A. A. (2014). The Analysis of Ontogenetic Spectrum of Heterogeneous Population. In: L. I. Weisfeld, A. I. Opalko, N. A. Bome, S. A. Bekuzarova (Eds.) Biological Systems, Biodiversity, and Stability of Plant Communities, ISBN 978-1-77188-064-0 (in press).
  • Glotov N. V., Sofronov G. Yu., Ivanov S. M., Teplykh A. A., Suetina Yu. G. (2014). Ontogenetic Spectra of Populations of Epiphytic Lichen Pseudevernia Furfuracea (L. ) Zopf. Modern Problems of Science and Education, 53(3), 1-10, ISSN 2070-7428.
  • Sofronov G. (2013). An optimal sequential procedure for a multiple selling problem with independent observations. European Journal of Operational Research, 225, 332-336, ISSN 0377-2217.
  • Priyadarshana M. W. J. R., Sofronov G. (2013). GAMLSS and Extended Cross-Entropy Method to Detect Multiple Change-Points in DNA Read Count Data, In: Muggeo VMR, Capursi V, Boscaino G, Lovison G (Eds.), Proceedings of the 28th International Workshop on Statistical Modelling, vol.1, 453-457, ISBN 978-88-96251-47-8.
  • Sofronov G. (2013). A hybrid algorithm for spatial small area estimation under models with complex contiguity. Proceedings of 2013 IEEE Symposium on Differential Evolution (SDE), 25-30, ISBN 978-1-4673-5847-7.
  • Manuguerra M., Sofronov G., Tani M., Heller G. (2013). Monte Carlo methods in spatio-temporal regression modeling of migration in the EU. Proceedings of 2013 IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr), 122-128, ISBN 978-1-4673-5847-7.
  • Sofronov G. Yu., Polushina T. V. (2013). Evaluating Optimal Stopping Rules in the Multiple Best Choice Problem Using the Cross-Entropy Method. Proceedings of the IASTED International Conference Modelling, Identification and Control (MIC 2013), 205-212, ISBN 978-0-88986-943-1, DOI: 10.2316/P.2013.794-018.
  • Polushina T. V., Sofronov G. Yu. (2013). A Hybrid Genetic Algorithm for Change-Point Detection in Binary Biomolecular Sequences. Proceedings of the IASTED International Conference on Artificial Intelligence and Applications (AIA 2013), 1-8, ISBN 978-0-88986-943-1, DOI: 10.2316/P.2013.793-026.
  • Trubyanov A. B., Sofronov G. Yu., Glotov N. V. (2013) Correlation structure of bilateral traits. In: Voskresenskaya O.L., Zhukova L.A. (Eds.), Principles and methods of biodiversity conservation, Proceedings of the Fifth International Research Conference,  vol. 2, 208-211, ISBN 978-5-94808-795-5.
  • Ivanov S. M., Sofronov G. Yu., Glotov N. V. (2013) Application of principal component analysis for study of ontogenetic spectrums of populations. In: Voskresenskaya O.L., Zhukova L.A. (Eds.), Principles and methods of biodiversity conservation, Proceedings of the Fifth International Research Conference,  vol. 2, 197-202, ISBN 978-5-94808-795-5.
  • Priyadarshana M. W. J. R., Sofronov G. (2012). A Modified Cross-Entropy Method for Detecting Change-Points in the Sri-Lankan Stock Market. In: Chen, B. M.; Khan, M. T. and Tan, K-K. (Eds.) The IASTED International Conference on Engineering and Applied Science (EAS2012), 321-326, DOI: 10.2316/P.2012.785-041.
  • Priyadarshana M. W. J. R., Sofronov G. (2012). The Cross-Entropy Method and Multiple Change-Points Detection in Zero-Inflated DNA read count data. In: Y. T. Gu, S. C. Saha (Eds.) The 4th International Conference on Computational Methods (ICCM2012), 1-8, ISBN 978-1-921897-54-2.
  • Sofronov G., Polushina T., Priyadarshana M. W. J. R. (2012). Sequential Change-Point Detection via the Cross-Entropy Method. In: B. Reljin, S. Stankovic (Eds.) The 11th Symposium on Neural Network Applications in Electrical Engineering (NEUREL2012), 185-188, ISBN 978-1-4673-1570-8.
  • Priyadarshana M. W. J. R., Sofronov G. (2012). A Modified Cross-Entropy Method for Detecting  Multiple Change-Points in DNA Count Data. Proceedings of the WCCI 2012 IEEE World Congress on Computational Intelligence, IEEE CEC, 1020-1027, ISBN 978-1-4673-1510-4.
  • Polushina T., Sofronov G. (2011). Change-Point Detection in Biological Sequences via Genetic Algorithm. Proceedings of the 2011 Congress on Evolutionary Computation (CEC 2011), IEEE, 1966-1971, ISBN 978-1-4244-7834-7.
  • Sofronov G. (2011). Change-Point Modelling in Biological Sequences via the Bayesian Adaptive Independent Sampler. International Proceedings of Computer Science and Information Technology. 5, 122-126, ISSN 2010-460X.
  • Evans G. E., Sofronov G. Yu., Keith J. M., Kroese D. P. (2011). Estimating Change-Points in Biological Sequences via the Cross-Entropy Method. Annals of Operations Research. 189 (1), 155-165, ISSN 0254-5330.
  • Sofronov G. Yu. (2010). Spatial small areas estimation: a comparison of Non-parametric EBLUP and M-quantile GWR models. In: A. Bowman (Ed.) Proceedings of the 25th International Workshop on Statistical Modelling, 509-514.
  • Sofronov G. Yu., Evans G. E., Keith J. M., Kroese D. P. (2009). Identifying Change-points in Biological Sequences via Sequential Importance Sampling. Environmental Modeling & Assessment. 14 (5), 577-584, ISSN 1420-2026.
  • Keith J. M., Kroese D. P., Sofronov G. Yu. (2008). Adaptive Independence Samplers. Statistics and Computing. 18 (4), 409-420, ISSN 0960-3174.
  • Keith J. M., Sofronov G. Yu., Kroese D. P. (2008). The Generalized Gibbs Sampler and the Neighborhood Sampler. In: Keller, A and Heinrich, S and Niederreiter, H (Eds.) Monte Carlo and Quasi-Monte Carlo Methods 2006. Springer-Verlag Berlin Heidelberg, Germany, Heidelberg, 537-547, ISBN 978-3-540-74495-5.
  • Nikolaev M. L., Sofronov G. Yu. (2007). A multiple optimal stopping rule for sums of independent random variables. Discrete Mathematics and Applications. 17 (5), 463-473, ISSN 0924-9265.
  • Gallagher M., Wood I., Keith J., Sofronov G. (2007). Bayesian Inference in Estimation of Distribution Algorithms. Proceedings of the 2007 Congress on Evolutionary Computation (CEC 2007), IEEE, 127-133, ISBN 978-142441340-9.
  • Nikolaev M. L., Sofronov G. Yu., Polushina T. V. (2007). A problem of sequential choice of multiple objects with given ranks. Bulletin of Higher Educational Institutions. The North Caucasus Region. Series Natural Sciences, 140 (4), 11-14, ISSN 0321-3005.
  • Sofronov G. Yu., Keith J. M., Kroese D. P. (2006). An optimal sequential procedure for a buying-selling problem with independent observations. Journal of Applied Probability. 43, 545-462, ISSN 0021-9002.
  • Sofronov G. Yu., Kroese D. P., Keith J. M., Nikolaev M. L. (2006). Simulations of thresholds in the multiple best choice problem. Surveys in Applied and Industrial Mathematics, 13 (6), 975-982, ISSN 0869-8325.
  • Sofronov G. Yu. (2005). Asymptotically d-optimal test of a postreriori change-point detection. Theory of Probability and Its Applications. 49 (2), 367-371, ISSN 0040-585X.
  • Sofronov G. Yu. (2002). Asymptotically d-optimal test of a change-point detection. Probability Theory and Its Applications, 46 (3), 547-548, ISSN 0040-585X.

Statistical Software

breakpoint: R-package

W. J. R. M. Priyadarshana, G. Sofronov. Multiple Break-Points Detection in array CGH Data via the Cross-Entropy Method. (submitted)

PhD scholarships

If you are interested in doing a Ph.D. at Macquarie under my supervision, and are eligible to apply for any of the scholarships listed below, then please contact me in advance of the closing dates
  • Domestic Candidates (Australian and New Zealand Citizens, Australian Permanent Residents) scholarships
  • International Candidates scholarships

Supervision of students

  • Dr Tatiana Polushina (completed her PhD degree in 2010, currently postdoc in the University of Bergen, Norway), principal supervsior
  • Mr Priyadarshana M. W. J. R. (PhD candidate since 2011), principal supervisor
  • Mr Sergey Ivanov (PhD candidate since 2010), adjunct supervisor 
  • More than 10 Master projects

Reviewing

  • Acta Mathematica Scientia
  • Australian and New Zealand Journal of Statistics
  • Bioinformatics
  • Computational and Structural Biotechnology Journal
  • Computers & Operations Research
  • Electronic Journal of Statistics
  • European Journal of Operations Research
  • IEEE Computational Intelligence Magazine
  • IEEE Transactions on Computational Biology and Bioinformatics
  • International Journal of Genomics